Industry executives and experts share their predictions for 2020. Read them in this 12th annual VMblog.com series exclusive.
By Chris Wolf, VP of the Advanced Technology Group, Office of the CTO,
VMware
What We Can Expect from Enterprise Tech
A new year (and a new decade!) is almost upon us. As we
close out the year, I like to take time to reflect not only on the past year,
but on the year to come. This past decade has seen a boom in enterprise
technology, from the massive growth of cloud computing to distributed edge
workloads, 5G networks and more. What could the next year, the next decade
hold?
In VMware's Office of the CTO, we are continually noodling
on new ideas and discussing them in partnership with numerous leaders within
our customer base and partner landscape. Based on those conversations, here's
what I see as not too far off on the horizon.
1. The Dawn of Hybrid Apps
A hybrid app is an application that's more or
less an aggregate of various microservices. It's a way to
build best-of-breed applications and differentiated services that can help
organizations stand out from competitors.
Imagine the ability to leverage data services
from one cloud provider and machine learning or analytics to another. Or
perhaps you have a business partner who has built services that want to run
adjacent to your data. For organizations, innovation is no longer limited by
what can be offered from a single cloud provider. A platform (like what we offer at VMware) can bring all these heterogeneous services
together and run these in ways you just can't do anywhere else.
Meetings with IT leaders throughout 2019 showed
me there's an appetite for the flexibility to build applications that combine
the best native cloud services and open source technologies.
2. Solutions at the Edge Come to Life
Organizations are looking for technology
partners to help solve problems and accelerate investments at the edge. I foresee
holistic edge solutions coming to market that will:
- Decrease
or neutralize edge computing costs.
- Consolidate
the amount of infrastructure needed at edge locations.
- Allow enterprises to deliver new technologies to remote
locations entirely in software, improving business velocity and
agility.
An example is a single hardware appliance that
provides software-defined WAN, while also running a few applications in
isolation. These will reduce costs by consolidating infrastructure and improve
network performance.
3. Specialized Hardware as a Shared Pool
When applications require specialized hardware
such as an FPGA or GPU, enterprises often have to dedicate servers to those
applications. In 2020, I expect to see the emergence of remotely connecting to
specialized hardware as key design principle.
When you combine hyperconverged infrastructure
with solutions, such as Bitfusion, that allow you to connect applications to
remote GPUs or FPGAs over Ethernet, you can take a modular approach to IT
infrastructure. You can also forgo the need to maintain hundreds of different
server builds to satisfy myriad application requirements. Going forward,
applications can remotely connect to that specialized hardware at the time they
need it.
4. The First Steps Toward Intrinsic Security
Malware is highly sophisticated and constantly
evolving. To combat it, an organization's security posture must be more
dynamic than the highly dynamic threats they face.
Security should be intrinsic to IT
infrastructure. The challenge is security systems and processes are far too
critical to disrupt all at once across an organization, and networking and
security professionals are risk-averse by nature, as they should be.
Instead, enterprises will slowly evolve toward
intrinsic security models, starting with a single application or new
project. We are reaching a point where network and security policy, along with
firewall rules, are simply attributes of an application. This means that rules
and policy are dynamically created at the time an application is initialized
and can be destroyed when the application is retired.
The ways in which we protect applications and
data are evolving, and it's hard to find IT professionals with these skillsets.
The best approach is to start small. Pick a new Kubernetes project, for
example, and go greenfield with modern, software-defined network and security
solutions. Your team can build knowledge organically and scale these new
methodologies across your enterprise over time.
5. Big Ideas for Small Devices
I think we'll see expanded use cases for smaller
devices, such as the Raspberry Pi 4, in the enterprise. It's less than $100,
but it's a powerful device with quite a bit of flexibility. Bringing
virtualization and other enterprise technologies to these devices, for even
more security and isolation at the edge, could introduce new opportunities to
innovate that we're not yet considering.
6. Machine Learning for the 99 Percent
Thus far, machine learning (ML) required a high
amount of data science and sophistication that's a bit out of reach for a
mainstream organization. For example, a small business can't hire its own team
of data scientists.
Soon, we'll see an increasing number of turnkey
ML services from cloud providers and open source communities. It will become
far more accessible, so businesses can apply ML models without a high
degree of expertise. The providers that succeed in making ML assessible for
organizations without data science expertise - the 99 percent - will be the
dominant players going forward.
7. Further Cloud Disaggregation
In some cases, it's impractical to move data to
the public cloud. So, why not move the cloud service to where the data
is?
We've already started to see cloud services run
independently of cloud data centers, such as running Amazon Relational Database
Service (RDS) on-premises. I expect to see far more examples of this in 2020
and beyond. The physical location of where a service runs ultimately becomes an
implementation detail that is dictated by business requirements and enforced
via policy.
8. Shared Services Platforms
In certain industries, bringing business
partners on board is often contingent upon the business partner bringing their
own hardware and software into the facility. A retailer's business partners
might have to bring their own desktop computers with their own software
solution into the store, which the IT team would then have to connect through
the firewall.
The problem with a business model where partners
need their own equipment, is that it limits innovation to partners that have
the capital to implement their solution. I expect to see the beginnings of
platforms that can live in a single location and run services from multiple
business partners, with isolation provided via virtualization software.
Multi-tenant shared services platforms at the
edge can be a big deal, as it can democratize innovation. These can allow
organizations to expand potential business partnerships to anyone with a great
idea, regardless of whether they have the capital to implement their
solution.
Platforms that allow enterprises to not only
onboard new business partners, but also potentially create new revenue streams
from leasing compute capacity and data access at the edge, will further
differentiate winners and losers in industries like retail and
manufacturing.
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About the Author
Chris
leads the Advanced Technology Group in the VMware Office of the CTO. The
Advanced Technology Group focuses on impactful near-term (1-3 year)
co-innovation through better alignment and collaboration with R&D product
teams, customers and technology partners, startups, and newly acquired
companies. It focuses on incubating emerging technologies with the goal of
building differentiated technology solutions and augmenting existing solutions.